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Handbuch der Deep-Learning-
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 eBay-Artikelnr.:365918295675
 Artikelmerkmale
- Artikelzustand
- ISBN-13
- 9781041102687
- Book Title
- Handbook of Deep Learning Models
- ISBN
- 9781041102687
Über dieses Produkt
Product Identifiers
Publisher
CRC Press LLC
ISBN-10
1041102682
ISBN-13
9781041102687
eBay Product ID (ePID)
15079882802
Product Key Features
Number of Pages
318 Pages
Language
English
Publication Name
Handbook of Deep Learning Models : Volume One: Fundamentals
Subject
Intelligence (Ai) & Semantics, Neural Networks
Publication Year
2025
Type
Textbook
Subject Area
Computers
Format
Hardcover
Dimensions
Item Length
9.7 in
Item Width
6.9 in
Additional Product Features
Intended Audience
College Audience
Illustrated
Yes
Table Of Content
Part - I - Fundamentals of Deep Learning 1. Introduction to Deep Learning 2. Machine Learning Fundamentals 3. Neural Networks Fundamentals Part - II -Deep Learning Models with Use Case Studies 4. Convolutional Neural Networks (CNNs) 5. Recurrent Neural Networks (RNNs) 6. Generative Adversarial Networks (GANs) 7. Radial Basis Function Networks (RBFNs) 8. Self Organizing Maps (SOMs)
Synopsis
This volume covers a comprehensive range of fundamental concepts in deep learning and artificial neural networks, making it suitable for beginners looking to learn the basics. Using Keras, a popular neural network API in Python, this book offers practical examples that reinforce the theoretical concepts discussed. Real-world case studies add relevance by showing how deep learning is applied across various domains. Topics such as layers, activation functions, optimization algorithms, backpropagation, convolutional neural networks (CNNs), data augmentation, and transfer learning are covered - providing a solid foundation for building effective neural network models. This book is a valuable resource for anyone interested in deep learning and artificial neural networks, offering both theoretical insights and practical implementation experience., This volume covers a comprehensive range of fundamental concepts in deep learning and artificial neural networks, making it suitable for beginners looking to learn the basics.
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